Inclusive Recommender Systems: Addressing Needs of Users with ADHD

Users’ experiences with technology are often shaped by their cognitive abilities, but formal evaluation of this phenomenon has been limited. In this study, we took a user-centered design approach with six participants with Attention Deficit Hyperactivity Disorder (ADHD) to evaluate their experiences with existing recommender systems and their needs for more inclusive recommenders. We found that while personalized recommendations helped our participants find community and social support, they also tended to impair participants’ impulsivity and self-regulation, impeding their daily lives. To address recommender systems’ lack of inclusivity, we co-designed two inclusive features: mode of use (focus/work versus explore) and notifications. The mode of use feature exemplifies users’ desire to explicitly enable or disable personalized recommendations to support self-regulation and reduce impulsivity. The notification feature represents a need to support ADHD users’ perception of time and memory. Our findings provide a first-person perspective of the recommender systems usage experiences of users with ADHD, and propose features to help make recommenders more inclusive of their needs.